This paper will partially solve the puzzle of implied volatility spreads from the perspective of short-selling (option-implied borrowing rate). Specifically, we use Chinese SSE 50 ETF options data to examine the relationship between the option-implied volatility spreads and option-implied borrow rate. Using nonparametric regression models, we find that there is a clear negative correlation between the implied volatility spreads and the implied borrowing rate. Furthermore, our results show that there is a significant nonlinearity between these two variables. Finally, it is interesting to note that the option volatility spreads are zero when the option prices include the short selling cost.

Fighting global warming has become a vital requirement for environmental sustainability. Green finance has gained popularity as a promising mechanism for transitioning to a lowcarbon economy. Thus, this paper investigates whether excess green financing increases renewable energy capacities and enhances environmental quality from 1992Q1 to 2020Q4 in China, one of the major CO2 emitters. We primarily used the method of moments-quantile regression with fixed-effect models. First, we found nonlinear U-shaped impacts of green finance on wind power capacities in all Chinese regions, thermal power capacities in the Western and Central areas, and hydropower capacities in Eastern China, respectively. Second, we confirmed an inverted U-shaped impact of green finance on CO2 emissions in the Eastern region but U-shaped effects in the Western and Central regions. The impacts of green finance were asymmetrical due to the heterogeneous distributions of renewable energy sources and environmental quality within and between regions. Green finance mostly improved environmental quality when certain conditions and thresholds were met. Third, green finance had substantial marginal effects on environmental quality in the least polluted provinces (Q.20) in Western China and the most polluted provinces (Q.80) in Eastern China. Finally, there were heterogeneous effects of oil prices, urbanization, foreign direct investments, and trade openness on renewable energy consumption and environmental quality across Chinese provinces. Accordingly, this study provides some policy recommendations for China’s sustainable development, a key example from which the international community can adjust its green policies.

This study investigates how digital transformation affects public sentiment toward firms on social media platforms in China. Using 2008-2022 data on Chinese listed companies and multivariate regression analysis, this paper identifies that digital transformation boosts positive online comments and sentiment. This relationship is mediated by gains in total factor productivity from digital initiatives. Moreover, concurrent green transformation positively moderates the effect, amplifying the impact of digital moves on online positive sentiment. Heterogeneous results reveal that the digital transformation effect on online positive sentiment is greater for state-owned, high-tech, and large companies. To our knowledge, this is the pioneering study to examine the linkage between corporate digital transformation and online public sentiment. The findings reveal whether, how, and when digital transformation shape more favorable public sentiment and online buzz. Companies can leverage digitalization, productivity improvements, and green development to foster positive perceptions and enhance their online reputation.

This article offers an in-depth exploration of the significance of research philosophy in the realm of management studies. It conducts a critical review of research philosophy, encompassing ontological, epistemological, and axiological dimensions, shedding light on their implications for management research. Traditional ontological perspectives, including realism, idealism, and pragmatism, are analyzed along with their influence on the field. Moreover, contemporary ontological debates are discussed, emphasizing their relevance to management research. The article also delves into the role of epistemology in shaping research methodologies, examining positivism, interpretivism, and critical realism as prominent frameworks. Emerging epistemological trends are explored, highlighting their impact on management research. Throughout the review, novel insights are presented, providing a foundation for future theoretical and empirical development. Researchers are encouraged to embrace ethical pragmatism, dynamic reflexivity, and epistemological pluralism, which can lead to more comprehensive and adaptable theories. The article concludes by calling for continued exploration and innovation in research philosophy to shape the future of management research. It emphasizes the dynamic nature of research philosophy and its potential to drive positive change in the management field. [译]本文深入探讨了研究哲学在管理研究领域中的重要性。文章对研究哲学进行了批判性综述，涵盖了本体论、认识论和价值论三个维度，并揭示了它们对管理研究的启示。文章分析了包括实在论、唯心主义和实用主义在内的传统本体论观点及其对该领域的影响，并讨论了当代本体论辩论，强调了它们与管理研究的关联性。此外，文章还深入探讨了认识论在塑造研究方法论方面的作用，审视了实证主义、解释主义和批判实在论等突出框架。文章还探讨了新兴的认识论趋势，强调了它们对管理研究的影响。在综述过程中，文章提出了新颖的观点，为未来的理论和实证研究奠定了基础。文章鼓励研究者采纳伦理实用主义、动态反思性和认识论的多元主义，这有助于形成更全面和更具适应性的理论。文章最后呼吁继续探索和创新研究哲学，以塑造管理研究的未来。它强调了研究哲学的动态性质及其在管理领域推动积极变革的潜力。

Capital misallocation is a crucial factor that hinders the high-quality development of the capital market. Taking mergers and acquisitions (M&A) cases of Chinese listed companies from 2007 to 2019 as samples, this study finds that there is a mismatch between the target firm’s profit quality and the M&A premium. Moreover, based on the dual perspective of acquirer and target motivations, this study demonstrates that the target firm’s insufficient motivation to improve its information quality is the primary cause of a capital mismatch. Factors that can enhance the motivation of the target, such as improving financial services and facilitating labour flow, are the cure for capital misallocation. It is a crucial study to understand China’s capital misallocation and of great theoretical and practical significance to understand the combination of efficient markets and effective governments in emerging markets.

Blockchain mania occurs in response to the quick rise of Bitcoin price in markets with cryptocurrencies circulation. However, Chinese government policies regarding the development of blockchain are inconsistent--block access to the offerings and exchanges of cryptocurrencies such as Bitcoins, but raise the blockchain technology to a strategic position. We empirically investigate whether the government’s inconsistent policies will lead to blockchain mania and how it affects the blockchainrelated firms’ activities and performance. Our results are threefold: First, the supportive policy can fully offset the negative effect due to the national boycott of cryptocurrencies. Second, Nonspeculative firms experience a stronger and long-standing positive reaction, while the effect on Speculative firms is transient and vanishes after receiving a definitive warning ten days later. Third, the market reaction to government support appears more pronounced among firms having established blockchain technology alliances, or being endorsed officially.

This study examines the impact of climate-transition risks on trade credits for Chinese listed companies from 2007-2017. We develop an index of county-level climate-transition risks faced by Chinese-listed companies using data on local carbon emissions and carbon sequestration when moving towards net zero carbon emissions. Our two-way fixed effects OLS regression results find that local firms facing greater climate-transition risks significantly reduce their trade credit financing. Specifically, a one standard deviation of increase in Risk leads to a 0.73% decrease in trade credit. This reduction is more pronounced for state-owned enterprises (SOEs), firms operating in less competitive industries, and those headquartered in regions without carbon trading markets. Our main finding is robust to a battery of sensitivity tests including the use of alternative measures and lagged independent variables. Results on an Instrumental Variable (IV) method and a differences-in-difference (DiD) analysis suggest a causal relationship between climate-transition risks on trade credit. Further analyses reveal two plausible channels for the effect: increased financial distress risk and enhanced access to bank credit.

This paper examines the different responses of local and foreign investors to host government risk perceptions in the context of extreme events. We develop COVID-19 attention indices that capture attention related to COVID-19 according to China Central Television (CCTV) news program and further construct the government’s risk perception (GRPC) measure about COVID-19. Given the cross-listed AH-shares in China, we find that GRPC caused the extreme movement of stock markets by applying the multi-quantile VaR Granger causality approach. The results show that the reaction of cross-listed stocks in the A-share market is more inflexible than that in the H-share market during the outbreak period of the pandemic, foreign investors follow GRPC as a weather vane than local investors, and both types of investors are more concerned about the pessimism of GRPC. In the period of epidemic normalization, local and foreign investors prefer the optimistic attitude conveyed by the Chinese government.

This study examines how short-sale constraints affect investors’ information acquisition and thereby shape stock price efficiency. By exploiting two settings that relax short-sale constraints in the US and China, respectively, we find that the removal of short-sale constraints increases investors’ information acquisition in both markets, but the effect is more prompt in China. Investors acquire value-relevant information, especially bad news, and improve their short-selling decisions in both markets. Lastly, information acquisition induced by the removal of short-sale constraints improves price efficiency. Our evidence shows that a reduction in trading frictions promotes information acquisition and improves price efficiency.

This article applies natural language processing (NLP) to extract and quan- tify textual information to predict stock performance. Leveraging an exten- sive dataset of Chinese analyst reports and employing a customized BERT deep learning model for Chinese text, this study categorizes the sentiment of the reports as positive, neutral, or negative. The findings underscore the predictive capacity of this sentiment indicator for stock volatility, excess re- turns, and trading volume. Specifically, analyst reports with strong positive sentiment will increase excess return and intraday volatility, and vice versa, reports with strong negative sentiment also increase volatility and trading volume, but decrease future excess return. The magnitude of this effect is greater for positive sentiment reports than for negative sentiment reports. This article contributes to the empirical literature exploring sentiment anal- ysis and the response of the stock market to news on the Chinese stock market.